Method | Regression Analysis

A comprehensive guide to regression analysis covering both continuous and discrete data, tailored for social science students involved in quantitative research.

1. Basic statistical concepts

• Probability & Inference
• Fundamental Distributions
• Measures of Association

2. Simple linear regression

• Basics of Simple Linear Regression
• Analysis of Variance
• The Lack of Fit F-test
• Correlation Coefficient
• Prediction
• R Example

3. Multiple linear regression

• Basics of Multiple Linear Regression
• Hypothesis test in MLR
• Data Transformation
• Interactions & Confounding
• R Example

4. Regression diagnosis

• Regression Diagnosis
• Model Evaluation & Building
• R Example

5. Logistic regression

• Contingency Table
• Introduction to Logistic Regression
• Analysis of Polytomous Data
• R Example

6. Generalized linear models

• Poisson Regression
• Generalized Linear Model
• R Example

7. Time series

• Time Series & Autocorrelation
• R Example

References

• [👩‍🏫 Course] 回归分析(台湾交通大学)
• [👩‍🏫 Course] STAT 501: Regression Methods
• [📖 Book] Montgomery, D.C., Peck, E.A., Vining, G.G. (2012). Introduction to Linear Regression Analysis (5th Edition). Wiley. (ILRA)
• [📖 Book] 谢宇. (2013). 回归分析(第2版). 社会科学文献出版社.
• [📖 Book] 唐启明. (2012). 量化数据分析. 社会科学文献出版社.